Can LLMs improve autonomous driving negotiation?
CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving
March 12, 2025
https://arxiv.org/pdf/2503.08683This paper introduces CoLMDriver, a system for cooperative autonomous driving using Large Language Models (LLMs). Vehicles negotiate driving decisions in natural language, refining their actions through an actor-critic feedback loop. Key points for LLM-based multi-agent systems include: language-based negotiation, an actor-critic framework for policy refinement, dynamic grouping of agents for efficient communication, and a parallel pipeline architecture to manage LLM inference latency. A new benchmark, InterDrive, is also introduced for evaluating cooperative driving systems.